To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .

To send content to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services.
Please confirm that you accept the terms of use.

Save Search

Most cited

These are the top ten most-cited articles for this title. Most-cited rankings are updated on a monthly basis and provided by CrossRef. The number in brackets represents the number of citations for each article.

The concept of an agent has become important in both artificial intelligence (AT) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents. For convenience, we divide these issues into three areas (though as the reader will see, the divisions are at times somewhat arbitrary). Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents. Agent architectures can be thought of as software engineering models of agents; researchers in this area are primarily concerned with the problem of designing software or hardware systems that will satisfy the properties specified by agent theorists. Finally, agent languages are software systems for programming and experimenting with agents; these languages may embody principles proposed by theorists. The paper is not intended to serve as a tutorial introduction to all the issues mentioned; we hope instead simply to identify the most important issues, and point to work that elaborates on them. The article includes a short review of current and potential applications of agent technology.

This paper is intended to serve as a comprehensive introduction to the emerging field concerned with the design and use of ontologies. We observe that disparate backgrounds, languages, tools and techniques are a major barrier to effective communication among people, organisations and/or software understanding (i.e. an “ontology”) in a given subject area, can improve such communication, which in turn, can give rise to greater reuse and sharing, inter-operability, and more reliable software. After motivating their need, we clarify just what ontologies are and what purpose they serve. We outline a methodology for developing and evaluating ontologies, first discussing informal techniques, concerning such issues as scoping, handling ambiguity, reaching agreement and producing definitions. We then consider the benefits and describe, a more formal approach. We re-visit the scoping phase, and discuss the role of formal languages and techniques in the specification, implementation and evalution of ontologies. Finally, we review the state of the art and practice in this emerging field, considering various case studies, software tools for ontology development, key research issues and future prospects.

Agent software is a rapidly developing area of research. However, the overuse of the word “agent” has tended to mask the fact that, in reality, there is a truly heterogeneous body of research being carried out under this banner. This overview paper presents a typology of agents. Next, it places agents in context, defines them and then goes on, inter alia, to overview critically the rationales, hypotheses, goals, challenges and state-of-the-art demonstrators of the various agent types in our typology. Hence, it attempts to make explicit much of what is usually implicit in the agents literature. It also proceeds to overview some other general issues which pertain to all the types of agents in the typology. This paper largely reviews software agents, and it also contains some strong opinions that are not necessarily widely accepted by the agent community.

Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing
such mappings has been the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works.
We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping.

This document describes COBRA-ONT, an ontology for supporting pervasive context-aware systems. COBRA-ONT, expressed in the Web Ontology Language OWL, is a collection of ontologies for describing places, agents and events and their associated properties in an intelligent meeting-room domain. This ontology is developed as a part of the Context Broker Architecture (CoBrA), a broker-centric agent architecture that provides knowledge sharing, context reasoning and privacy protection supports for pervasive context-aware systems. We also describe an inference engine for reasoning with information expressed using the COBRA-ONT ontology and the ongoing research in using the DAML-Time ontology for context reasoning.

Case-Based Reasoning (CBR) is a relatively recent problem solving technique that is attracting increasing attention. However, the number of people with first-hand theoretical or practical experience of CBR is still small. The main objective of this review is to provide a comprehensive overview of the subject to people new to CBR. The paper outlines the development of CBR in the US in the 1980s. It describes the fundamental techniques of CBR and contrasts its approach to that of model-based reasoning systems.1 A critical review of currently available CBR software tools is followed by descriptions of CBR applications both from academic research and, in more detail, three CBR systems that are presently being used commercially. Each of the three commercial case studies highlights features that made CBR particularly suitable for the application. Moreover, the last case study describes a development methodology for implementing CBR systems. The paper concludes with a research agenda for CBR. A detailed categorized bibliography of CBR research is provided in a companion paper (Marir & Watson, 1994).

Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.

Many researchers have demonstrated that the organizational design employed by an agent system can have a significant, quantitative effect on its performance characteristics. A range of organizational strategies have emerged from this line of research, each with different strengths and weaknesses. In this article we present a survey of the major organizational paradigms used in multi-agent systems. These include hierarchies, holarchies, coalitions, teams, congregations, societies, federations, markets, and matrix organizations. We will provide a description of each, discuss their advantages and disadvantages, and provide examples of how they may be instantiated and maintained. This summary will facilitate the comparative evaluation of organizational styles, allowing designers to first recognize the spectrum of possibilities, and then guiding the selection of an appropriate organizational design for a particular domain and environment.

Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and domains. Following a brief overview of the traditional problem-solving cycle in CBR, we examine the cognitive science foundations of CBR and its relationship to analogical reasoning. We then review a representative selection of CBR research in the past few decades on aspects of retrieval, reuse, revision and retention.

Negotiation is essential in settings where autonomous agents have conflicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which influence each others' states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.